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Bright field microscopic cells counting method for BEVS using nonlinear convergence index sliding band filter
BACKGROUND: The Baculovirus Expression Vector System (BEVS) is a very popular expression vector system in gene engineering. An effective host cell line cultivation protocol can facilitate the baculovirus preparation and following experiments. However, the counting of the number of host cells in the...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4221726/ https://www.ncbi.nlm.nih.gov/pubmed/25342097 http://dx.doi.org/10.1186/1475-925X-13-147 |
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author | Sui, Dong Wang, Kuanquan Park, Heemin Chae, Jinseok |
author_facet | Sui, Dong Wang, Kuanquan Park, Heemin Chae, Jinseok |
author_sort | Sui, Dong |
collection | PubMed |
description | BACKGROUND: The Baculovirus Expression Vector System (BEVS) is a very popular expression vector system in gene engineering. An effective host cell line cultivation protocol can facilitate the baculovirus preparation and following experiments. However, the counting of the number of host cells in the protocol is usually performed by manual observation with microscopy, which is time consuming and labor intensive work, and prone to errors for one person or between different individuals. This study aims at giving a bright field insect cells counting protocol to help improve the efficient of BEVS. METHOD: To develop a reliable and accurate counting method for the host cells in the bright field, such as Sf9 insect cells, a novel method based on a nonlinear Transformed Sliding Band Filter (TSBF) was proposed. And 3 collaborators counted cells at the same time to produce the ground truth for evaluation. The performance of TSBF method was evaluated with the image datasets of Sf9 insect cells according to the different periods of cell cultivation on the cell density, error rate and growth curve. RESULTS: The average error rate of our TSBF method is 2.21% on average, ranging from 0.89% to 3.97%, which exhibited an excellent performance with its high accuracy in lower error rate compared with traditional methods and manual counting. And the growth curve was much the manual method well. CONCLUSION: Results suggest the proposed TSBF method can detect insect cells with low error rate, and it is suitable for the counting task in BEVS to take the place of manual counting by humans. Growth curve results can reflect the cells’ growth manner, which was generated by our proposed TSBF method in this paper can reflected the similar manner with it’s from the manual method. All of these proven that the proposed insect cell counting method can clearly improve the efficiency of BEVS. |
format | Online Article Text |
id | pubmed-4221726 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-42217262014-11-07 Bright field microscopic cells counting method for BEVS using nonlinear convergence index sliding band filter Sui, Dong Wang, Kuanquan Park, Heemin Chae, Jinseok Biomed Eng Online Research BACKGROUND: The Baculovirus Expression Vector System (BEVS) is a very popular expression vector system in gene engineering. An effective host cell line cultivation protocol can facilitate the baculovirus preparation and following experiments. However, the counting of the number of host cells in the protocol is usually performed by manual observation with microscopy, which is time consuming and labor intensive work, and prone to errors for one person or between different individuals. This study aims at giving a bright field insect cells counting protocol to help improve the efficient of BEVS. METHOD: To develop a reliable and accurate counting method for the host cells in the bright field, such as Sf9 insect cells, a novel method based on a nonlinear Transformed Sliding Band Filter (TSBF) was proposed. And 3 collaborators counted cells at the same time to produce the ground truth for evaluation. The performance of TSBF method was evaluated with the image datasets of Sf9 insect cells according to the different periods of cell cultivation on the cell density, error rate and growth curve. RESULTS: The average error rate of our TSBF method is 2.21% on average, ranging from 0.89% to 3.97%, which exhibited an excellent performance with its high accuracy in lower error rate compared with traditional methods and manual counting. And the growth curve was much the manual method well. CONCLUSION: Results suggest the proposed TSBF method can detect insect cells with low error rate, and it is suitable for the counting task in BEVS to take the place of manual counting by humans. Growth curve results can reflect the cells’ growth manner, which was generated by our proposed TSBF method in this paper can reflected the similar manner with it’s from the manual method. All of these proven that the proposed insect cell counting method can clearly improve the efficiency of BEVS. BioMed Central 2014-10-24 /pmc/articles/PMC4221726/ /pubmed/25342097 http://dx.doi.org/10.1186/1475-925X-13-147 Text en © Sui et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Sui, Dong Wang, Kuanquan Park, Heemin Chae, Jinseok Bright field microscopic cells counting method for BEVS using nonlinear convergence index sliding band filter |
title | Bright field microscopic cells counting method for BEVS using nonlinear convergence index sliding band filter |
title_full | Bright field microscopic cells counting method for BEVS using nonlinear convergence index sliding band filter |
title_fullStr | Bright field microscopic cells counting method for BEVS using nonlinear convergence index sliding band filter |
title_full_unstemmed | Bright field microscopic cells counting method for BEVS using nonlinear convergence index sliding band filter |
title_short | Bright field microscopic cells counting method for BEVS using nonlinear convergence index sliding band filter |
title_sort | bright field microscopic cells counting method for bevs using nonlinear convergence index sliding band filter |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4221726/ https://www.ncbi.nlm.nih.gov/pubmed/25342097 http://dx.doi.org/10.1186/1475-925X-13-147 |
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